Temporal Coherence Changes of Typical Urban Features Based on Sentinel-1A Data

Abstract

Using the principle of radar interferometry, we analyzed the temporal coherence changes of five typical ground features (residential areas, vegetation, bare soil, bridges, and factories and warehouses) in urban areas of Beijing using 29 images from Sentinel-1A equipped with a C-band synthetic aperture radar (SAR) sensor over one year. The results of the study showed the following. (1) Among the five typical ground features, the coherence of vegetation was the lowest. Owing to changes in its state and atmospheric conditions, the coherence of vegetation fluctuated sharply over the year. The coherence of factories and warehouses was the highest and relatively stable over the year. (2) Classifying the five typical ground features into artificial and natural features, we found that the artificial features of factories and warehouses, residential areas, and bridges maintained a high degree of coherence over the year. Among them, the coherence of residential areas was the most stable. The natural features of vegetation and bare soil were affected by the changes in their states and atmospheric conditions over the year. The research results can be used for the classification of land use types, the statistical analysis of urban green coverage, and the extraction of points with high coherence in long-term surface deformation inversion.

Monitoring Scheme of Liquified Natural Gas External Tank Using Air–Space–Land Integration Multisource Remote Sensing

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